Triple
T9019266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chip Tolentino |
E215671
|
entity |
| Predicate | musicalTheatreType |
P85741
|
FINISHED |
| Object | tenor role |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: tenor role | Statement: [Chip Tolentino, musicalTheatreType, tenor role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicalTheatreType Context triple: [Chip Tolentino, musicalTheatreType, tenor role]
-
A.
musicalTheatreWorkType
Indicates the specific type or category of a musical theatre work that characterizes the nature of the production.
-
B.
musicalTheatreWork
Indicates that one entity is a musical theatre work (such as a musical or operetta) associated with or characterized by the other entity.
-
C.
theatreType
Indicates the specific category or kind of theatre associated with an entity, such as its format, style, or operational model.
-
D.
theatricalGenre
Indicates the specific theatrical genre or style to which a performance, play, or production belongs.
-
E.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca83a38aa88190bf1bb80c4548b5e2 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a4085848190a6aa440e6307e93d |
completed | April 1, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f6dec4081909379bd57c02a5710 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:07 p.m.